Digital Commons Network^™

An Educational Approach To Mitigating Stormwater Debris Pollution In The Great Lakes Basin, Autumn Potts

Theses

Accumulation of anthropogenic debris (AD) in the environment, especially plastic, is a pervasive issue that impacts human communities and ecosystems worldwide. Since AD pollution at every scale stems from human activities, its mitigation is contingent on analyzing and modifying the scale-dependent drivers of human behavior surrounding this issue. Although the underlying mechanisms driving litter input and accumulation are not well understood, these patterns suggest a need for hyperlocal solutions. Because environmental education (EE) fosters a significant influence on environmental knowledge, attitudes, and behaviors, it can play an important role in the mitigation of debris input and littering behavior. One method …

The Impact Of Artificial Intelligence On Employee Attrition And Organizational Profitability, Saeed Almehairi

Theses

Artificial Intelligence (AI) has become a transformative force in the modern workplace, reshap- ing decision-making processes, enhancing operational efficiency, and influencing the dynamics of human resource management. One of the critical areas where AI demonstrates substantial potential is in predicting, managing, and mitigating employee attrition. Employee attrition remains a pressing organizational challenge, incurring substantial costs in recruitment, training, and lost productivity. This research investigates the dual impact of AI on employee attrition and organizational profitability, exploring both the opportunities and the challenges that arise from its integration into human resource and business operations. The study examines how AI-driven predictive analytics …

Social Media's Impact On Female Generation Alpha's Beauty Standards And Consumer Habits, Matisen O'Brien

Theses

This study examines how social media shapes beauty standards and consumer behaviors among female Generation Alpha (ages 7–13). As the first generation fully immersed in digital culture, these young girls face early exposure to influencer marketing, algorithmic promotion, and adult beauty practices, which influence their skincare routines and product preferences. The research highlights the decline of child-centered physical spaces, intensifying their engagement with digital platforms. Using a mixed-methods approach focused on a subgroup of female gymnasts, the study combines quantitative surveys and qualitative analysis to reveal how social media affects identity formation, consumer choices, and related mental health concerns. Results …

These Yellow Stars Of Ours, Vinh Hong Nguyen

Theses

These Yellow Stars of Ours is an experimental documentary that traces the intertwined histories of Thaun and Nam Nguyen as they flee war-torn Vietnam, fall in love, and build a life in Western New York. Through their accounts and those of their two sons, the film explores the complexities of generational trauma and the ongoing experience of bicultural straddling—the negotiation between inherited Vietnamese identity and the shaping influence of an American upbringing. The project examines how trauma, memory, and cultural displacement circulate across generations, shaping identity in both visible and invisible ways. Methodologically, the film is structured around the conceptual …

Comparative Analysis Of Machine Learning Models For Spam Email Detection, Rashed Almarri

Theses

The current research examines one of the most effective approaches to spam email detection based on machine learning and natural language processing (NLP). The study is placed in the context of the rising cyber threats and the influx of emails, where the spam/ham data is to be classified correctfully using the combination of the Logistic Regression, NLP (including tokenization, lemmatization, and TF-IDF vectorization). The questions of the research were devoted to the efficiency of such an approach and the interpretation of its results. The data used are obtained by a publicly available Kaggle data set that contains 5,572 labeled email …

The Role Of Technology In Modernizing Prison Management Systems, Essa Anwahi

Theses

This thesis examines the role of technology in modernizing prison management systems and improving operational efficiency, security, and decision-making. It explores how digital technologies and data analytics can address challenges in traditional prison management, such as inefficient processes and limited data utilization. The study highlights the potential of technology-driven solutions to enhance system performance and support more effective management practices within correctional facilities.

Security Vulnerabilities In Cloud Storage: A Comparative Study Of Google Drive, Dropbox, And Onedrive, Sultan Majid Alshamsi

Theses

In recent years, use of internet has increased manifold. People have started creating more data, and instead of saving it locally, people have started preferring storing it “online”. Companies are also following the same path to maintain accessibility and availability of their data. Thus, data has become a central part of our lives. People, companies, and institutions rely heavily on cloud storage solutions these days for managing their data. Some of the main cloud storage solution are Google Drive, Dropbox, and OneDrive. These are sophisticated solutions developed by tech giants, and general expectation of the public is that these solutions …

A Comparison Of Fixed And Repetitive Models During Imitation Training In Children With Developmental Delays In A School Setting, Laci Fletcher

Theses

Imitation training is commonly recommended in applied behavior analytic literature to address deficits in imitative skills. Few studies have directly compared imitative models to identify the most efficient and effective teaching arrangement to facilitate imitative skills (Deshai & Vollmer, 2019; Halbur et al., 2023). Previous results are inconclusive, and the authors recommended further research comparing the effect of fixed and repetitive models. Therefore, the present study was a replication of Halbur et al. (2023) and addressed limitations suggested by the authors. We examined whether components of imitative models affected the efficiency of the model type and reduced faulty stimulus control …

Ecotheology For Kids, Lana Glenn

Theses

This project includes research into the eco-anxiety of children and how ecotheology may help ease the children’s minds. This project is meant as a sign of hope in the climate crisis; there are so many reasons to look forward to ecological improvements for the Earth. As adults, we should remind children of these reasons to be hopeful for the future. This 24-page book has illustrations with prayers to help calm the readers, while the cover is informational and inviting.

Frameworks Of Genius: Fresco, Labor, Scaffolding, And Patronage In The Making Of Michelangelo's Sistine Chapel Ceiling, Jackelyn Eileen Adkins

Theses

This thesis examines how the materiality of production and the patronage of Pope Julius II influenced the visual and conceptual outcome of Michelangelo’s ceiling frescoes in the Sistine Chapel. It argues the physical demands of the fresco medium, the architectural constraints of the chapel, and the material infrastructure, such as the pigments, scaffolding, and spatial dynamics related to the political, theological, and ideological imperatives of papal authority. The materials served as a symbolic extension of Pope Julius II’s ambitions, embedding his message directly into the frescoes. By foregrounding the complex web of labor and materials that supported the project, this …

Accessible Preservation: Developing A Low-Cost, Iiif-Compliant Workflow For Small Art Collections, Robyn Palescandolo

Theses

This project explores the development of an affordable, standards-based digital collections management system designed for small galleries, independent artists, and emerging institutions. Using the artist’s own studio collection as a case study, the research integrates accessible hardware and open-source technologies, including the International Image Interoperability Framework (IIIF), Artwork Archive, GitHub Pages, and the Internet Archive, to establish a transparent, replicable workflow for cataloguing and publication. The project demonstrates how interoperability, metadata consistency, and open access can be achieved without reliance on costly proprietary systems, such as TMS Collections or PastPerfect.

The workflow includes high-resolution image capture, 3D scanning, data normalization, …

Asymptote, Aybuke Yilmazer

Theses

Asymptote is a short film that is an expression of mankind’s emotional consumption through confusing love with sex. This film is a frame-by-frame hand-drawn animation that combines digital and analog techniques. It was produced between August 2024 and April 2025, and its music was re-produced in August 2025. This paper is a written declaration of the motives and intentions of the director, Aybuke Yilmazer, in making this film, and analyzes the filmmaking process. The text of the thesis is in third person except for the self-evaluation section.

Exploring Denitrification In Wetland Nitrogen Cycling And Biostimulant-Based Agricultural Strategies To Improve Ecosystem Health, Alexander Bechtel

Theses

The overuse of fertilizers has doubled the amount of reactive nitrogen in the environment. Agricultural runoff then carries these pollutants into the waterways eventually causing severe ecological damage such as the Gulf of Mexico dead zone. Nitrogen plays an important role in all life on this planet, here we describe two complementary projects that investigate ways to mitigate nitrogen pollution. The first project investigates denitrification rates in soil after the Len Small Levee breached in 2016 which reconnected the Dogtooth Bend Floodplain with the Mississippi briefly. The denitrification process that began in the hydrologically activated soils was hypothesized to be …

Echo’S Repertoire: Performing Science Fiction And Trans Care Models, Juniper Blue

Theses

Echo’s Repertoire is a mixture of a passion piece and a call for more work with performing science fiction. It focuses on interpersonal communication within trans studies and the experiences of transgender individuals and myself. Echo’s Repertoire is also an example of the Lyrical Model proposed by Awkward-Rich as a new model for trans affirming speech. The show is laid out non-linearly and follows along with Echo as he starts to build new relationships with the advice of his spaceship ai, Eep, who is a previous version of himself prior to transformation (transition).

Embedded Sensor Design For Non-Robust Delay Testing, Presh Jayawardana Manannaidelage

Theses

Current delay testing methodologies for integrated circuits face critical limitations, asrobust tests remain unachievable for most paths, forcing reliance on Non-Robust (NR) tests that suffer from unrealistic single-fault assumption, the path under test non being sensitized, and vulnerability to hazard-induced errors. This thesis propose a built-in sen- sor to detect delayed hazards and a sensor to diagnose circuits in the presence of those hazards resulting reliable detection. This thesis intends to propose 2 sensors for non-robust test-based monitoring and test- ing. The first sensor discussed is for IC testing with NR tests. This sensor is capable of detecting any full-swing …

Unmasking Corruption And Bribery Using Predictive Analytics, Maha Salem

Theses

The initiative (Unmasking Corruption and Bribery Using Predictive Analytics) aims to identify employees in government sectors who commit corruption and bribery by addressing issues such as the lack of transparency, fairness, equality, and public trust, as well as weakened loyalty and poor reputation. This project focuses on data analytics and predictive modeling to detect suspicious or high-risk employee behaviors related to corruption and bribery. The main objective is to reduce these unethical activities in government sectors, strengthen integrity, and promote transparency and public trust through predictive capabilities. It also seeks to raise awareness about how serious and harmful these crimes …

Predictive Maintenance For It Equipment Using Machine Learning Models, Rashed Khalid Alshirawi

Theses

Predictive maintenance was recently introduced as a paradigm shift in the field of smart manufacturing, and it allows organizations to predict equipment failures and streamline maintenance planning based on the data-driven insights. The present work addresses the concept of the implementation of a decision tree-based predictive maintenance model based on AI4I 2020 Predictive Maintenance Dataset, a simulated environment of an actual industry through sensor data including temperature, torque, rotational velocity, and toolwear. The study uses a quantitative approach that is based on positivism philosophy, which is the focus on objectivity, empirical validation, and statistical testing of the model performance. Synthetic …

Predicting Inmate Overcrowding To Improve Facility Management, Mayed Ali Alameri

Theses

Overcrowding is a major challenge to correction systems because the conventional forecasting techniques are inaccurate and inadequate in most cases. This paper will solve this by constructing and testing a machine learning-based model to predict facility-level overcrowding. With the use of the XGBoost Regressor model on a dataset comprising of U.S. correctional facilities, the research identified key structural drivers but showed that the static facility attributes alone have limited predictive power (r-square approx 0.18) The discussion shows that overcrowding is non-linear, and a complicated problem not confined to the facility characteristics but to the larger, non-measurable regional influences, of which …

Strainx : A Technical Exploration Of Cinema4d'S Native Particle System In An Experimental Title Sequence, Farah Ahmad

Theses

This paper presents a practice-based investigation into the capabilities of Cinema 4D’s native particle system through the creation of an experimental title sequence titled StrainX. The project was conceived as a technical and aesthetic exploration, prioritizing abstraction, form, and motion over narrative content. Through iterative testing and simulation, the study examines how Cinema 4D’s built-in particle, geometry, and material tools can generate visually complex results without relying on third-party plugins, such as X-Particles. All assets, simulations, and textures were developed natively within Cinema 4D, allowing for a unified and efficient workflow. The methodology emphasizes procedural experimentation, simulation caching using Alembic …

Optimizing Waste Management And Recycling Patterns Using Data Analytics, Mohammad Omar Almarri

Theses

The increasing pace of urbanisation and consumption has increased the burden of waste generation in the world and it is a huge burden on the current waste management systems. The United Arab Emirates (UAE) is a region that is intensifying this challenge through the accelerated urbanization, high sustainability targets, and the necessity of effective recycling policies. The thesis that is being examined explores the ways in which the data analytics can be utilized to streamline waste management and recycling trends, emphasizing the enhancement of the collection process, forecasting the trends in the waste generation as well as facilitating the use …

Geometric Deviation Prediction In Additively Manufactured Parts Using Conditional Generative Adversarial Networks Under Varying L-Pbf Process Parameters, Subigyamani Bhandari

Theses

The progress in metal AM technology has enabled printing parts with thin features and intricate geometries. Predicting and reducing metal AM part geometrical deviations to narrow down the difference between printed and designed structure still poses a problem. This work explores changes in laser speed, laser power, and hatch spacing affecting geometrical deviations in parts made using laser powder bed fusion (L-PBF) and places an emphasis on how to predict geometrical defects in the AM parts. Sliced images obtained from CAD designs and printed parts to capture the effect of various L-PBF process parameters are utilized to create a dataset. …

Prediction Of Geometric Deviation In Additively Manufactured Tpms Lattice Structures Using Non-Destructive Evaluation And Conditional Generative Adversarial Networks, Prateek Neupane

Theses

Metal 3D printing has emerged as a widely used additive manufacturing method, finding applications across numerous industries and research areas. However, its application is often hindered by geometric inaccuracies and surface quality issues resulting from the complex interplay of laser power, melt pool behavior, and cooling characteristics. These inconsistencies have a significant impact on the design and functionality of printed parts, affecting structural integrity and dimensional accuracy. Thus, an effective data-driven approach is crucial to predict these deviations before manufacturing. This study proposes a methodology that incorporates Non-destructive evaluation techniques, like in-situ monitoring and X-ray CT scan, with Conditional Generative …

Exploring The Adoption Of Quality 4.0: A Qualitative Study Of Industry Practices And Barriers, Tama Rani Sarker

Theses

The emergence of Industry 4.0 has revolutionized quality management, introducing Quality 4.0 as a framework that integrates digital technologies with established quality principles. Despite its potential to enhance operational efficiency and decision-making, many organizations face challenges in adopting Quality 4.0, including skill gaps, resource constraints, and cultural resistance. This qualitative study explores industry practices, barriers, and enablers of Quality 4.0 implementation through surveys and interviews with quality professionals in southern Illinois manufacturing companies. Using a phenomenological approach, five major themes emerged: employee skillset, training, technology integration, quality tools, and supply chain management. Findings reveal that successful adoption depends on workforce …

Flood Susceptibility Assessment Through Gis Integrated Analytical Hierarchy Process And Machine Learning Models, Sujan Shrestha

Theses

Flooding is among the most destructive natural disasters globally, and it inflicts severe damage on both natural environments and human-made structures. The frequency of floods has been increasing due to unplanned urbanization, climate change, and changes in land use. Flood susceptibility maps help identify at-risk areas, supporting informed decisions in disaster preparedness, risk management, and mitigation. This study aims to generate a flood susceptibility map for two regions: Davidson County of Tennessee using an integrated geographic information system (GIS) and analytical hierarchical process (AHP), and the Briar Creek watershed of Mecklenburg County, North Carolina using an integrated GIS and machine …

Beyond The Mozart Effect: How Musical Experience And Emotional Response Shape Individual Differences In Spatial Reasoning, Connor Watkinson

Theses

Research on the Mozart effect (the short-term enhancement of spatial-temporal reasoning after music listening) has yielded inconsistent results, often due to overlooking individual differences and using limited stimuli. This study examined multiple musical conditions (popular lyrical, classical, and white noise control) while considering the moderating roles of musical experience and the mediating influence of emotional responses. Undergraduate participants (N = 162) completed spatial reasoning assessments before and after an eight-minute listening session, alongside measures of musical background, listening habits, mood, and music-evoked emotions.Analyses revealed no overall difference in spatial reasoning improvement between music and white noise conditions. However, substantial individual …

Early Diabetes Prediction Using Machine Learning: A Comparative Study Of Classification Models, Ahmed Abdelqadir Bawazir

Theses

The current dissertation investigates the application of machine learning in diabetes prediction at early stages through a comparison of the performances of three classification models, including Logistic Regression, Decision Tree, and Random Forest. Inspired by the increased and spread cases of diabetes worldwide, the research objective is to facilitate early diagnosis by providing interpretable and accurate predictive models. Based on Pima Indians Diabetes Dataset containing 768 clinical records, the research implemented data preprocessing including KNN imputation and outlier processing, feature scaling, and formation of interaction features. Quantitative and comparative approach was made to train and test the models based on …

Three Forks, Virginia Van Enckevort

Theses

Three Forks is a thesis drama series about a 19th-century woman sent West to live with her estranged family in Muscogee, a lawless town where justice bends to power and survival means learning the game — or being buried by it. As we follow our lead, Eleanor Davis, out West and eventually her settlement into town, we gain a look into her new world, one where tribal council contend with encroaching U.S. jurisdiction and where settlers, freedmen, and railroad men jostle for influence in a town on the brink of statehood. The many fabled stories and myths about the West …

Analyzing The Hidden Impact Of Work Stress On Mental Health, Shaikha Aljabry

Theses

Occupational stress and deteriorating mental health constitute an increasing issue in the global community, and the problem of how job demands, personal resources, and cognitive processes interrelate to determine employee well-being is hardly known. This dissertation will study these dynamics by incorporating theory-driven Structural Equation Modeling (SEM) with data-driven Machine Learning (ML) methods that offer explanatory and predictive information. The study examines the influences of job demands, personal resources, effort–reward imbalance (ERI), emotional labor, cognitive appraisal, and social support on the stress and mental health outcomes of a sample of 5,000 employees working in various industries and regions of the …

Trust Calibration In Human-Ai Teaming: Within-Session Dynamics, Transparency, And Performance Effects, Mohamed Ahmed Aljaziri

Theses

Trust plays a decisive role in the effectiveness of human-AI teams, particularly in tasks that depend on coordinated decision-making under uncertainty. While prior research acknowledges that trust in automation is dynamic, current work provides limited insight into how trust evolves within an interaction, what causes it to become miscalibrated, and how transparency affects these processes. This thesis examines trust calibration in a controlled 2-D grid-world search-and-rescue environment, where 54 participants collaborated with an AI teammate presented through four communication modes based on the Ability, Benevolence, and Integrity (ABI) framework. The study uses secondary analysis of experimental data to observe: (1) …

Practice?, Pei Chen

Theses

3D animation is a combination of art and technique. Art serves to convey your perspective, express beauty, tell stories, and more. However, to accomplish these goals, we need solid technical support. Only by paying attention to both, can we achieve excellent results. The title of this film is “Practice?”, which is a deliberate pun. On one hand, "practice" refers to the martial arts training sequences of the character, during which his master provides guidance, intervenes in his movements, and progressively increases the difficulty. On the other hand, "practice" also symbolizes my own artistic and technical experimentation—exploring and refining skills in …